Software Engineering Manager II, Agentic Planning and Memory

Design and architect available systems for agentic planning and memory management.Ensure the reliability and performance of agentic workflows and memory retrieval systems.Define the long-term technical roadmap for the agentic memory layer and planning infrastructure.Lead system designs that enable autonomous tool-calling and context awareness.Collaborate across teams to integrate function-calling capabilities into core workspace products. Manage organizational growth, staffing, and technical strategy for the agentic planning team.Minimum qualifications:Bachelor's degree or equivalent practical experience.8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).5 years of experience in leading machine learning (ML) design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).3 years of experience in a technical leadership role.2 years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI related concepts (language modeling, computer vision).2 years of experience in a people management or team leadership role.Preferred qualifications:Master’s degree or PhD in engineering, computer science, or a related technical field.3 years of experience working in a changing organization involving cross-functional or cross-business projects.Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally. The Agentic Planning and Memory team is transforming Google Workspace into a proactive digital partner. The team's mission is to build next-generation agentic capabilities focused on two core pillars: developing advanced general function-calling approaches that allow agents to autonomously execute workflows, and building an agentic memory layer that enables agents to retain and utilize context more efficiently to improve accuracy, personalization, and latency.AI will change the future of work in profound ways, and our products— Gmail, Docs, Drive, Calendar, Sheets, Vids and Meet are at the forefront. From pre-computed summaries for email threads, summaries for meetings, and videos created from a document using lifelike AI avatars, our AI opportunity is huge. Our mission is to meaningfully connect people so they can create, build, and grow together and as part of the team you can build how productivity tools should work 5-10 years into the future. You will work with model builders (Google DeepMind), work with exceptional leaders, and have the ability to impact billions of users across the world.Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $207000 - $300000 (USD) + 20% bonus target + equity + benefitsLearn more about benefits at Google.Bachelor's degree or equivalent practical experience.8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).5 years of experience in leading machine learning (ML) design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).3 years of experience in a technical leadership role.2 years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI related concepts (language modeling, computer vision).2 years of experience in a people management or team leadership role.